Developing and Evaluating the S.A.F.E.R. Near Water Program: An Intervention to Enhance Beliefs Relevant to Supervision and Drowning Risk in Parents With Young Children in Swimming Lessons
Bibliographic record
Abstract
The current study aimed to develop and evaluate the S.A.F.E.R. Near Water program, an evidence-based and theory-driven intervention targeting parent beliefs relevant to keeping children safe around water. Parents with children aged two through five years who were enrolled in lessons at both public and private swim organizations participated. Within each organization, parents were assigned to either an Intervention or Control Condition. All parents completed the same questionnaire measures at the beginning and end of their child’s swim lesson period. Parents in the Intervention Condition participated in the S.A.F.E.R. Near Water program, which comprised in-person educational seminars, informational handouts, and posters reinforcing key safety messages. Results revealed that S.A.F.E.R. Near Water successfully communicated most intended messages and was well received by parents. It significantly improved parental perceptions related to supervision, drowning risk, optimism bias, and water safety. These findings are encouraging for the use of a multifaceted, parent-focused, educational program alongside swim programming to promote closer adult supervision of children around water.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".